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Machine Translation
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Machine translation is the task of translating a sentence in a source language to a different target language.
Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.
One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.
<span style="color:grey; opacity: 0.6">( Image credit: Google seq2seq )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lt-nlp-lab-unibo/newssd-eng
공식 코드A Corpus for Sentence-level Subjectivity Detection on English News Articles
https://github.com/luferrer/DCA-PLDA
공식 코드A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognition
https://github.com/luka-group/prix-lm
공식 코드Prix-LM: Pretraining for Multilingual Knowledge Base Construction
https://github.com/lumia-group/distance_transformer
공식 코드Syntax-guided Localized Self-attention by Constituency Syntactic Distance
https://github.com/luosx18/biomedical-sentence-aligner
공식 코드Sentence Alignment with Parallel Documents Facilitates Biomedical Machine Translation
https://github.com/luxinyu1/trans-ss
공식 코드An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages
https://github.com/lvapeab/interactive-keras-captioning
공식 코드A Neural, Interactive-predictive System for Multimodal Sequence to Sequence Tasks
https://github.com/lvapeab/nmt-keras
공식 코드https://github.com/lvapeab/sentence-selectioNN
공식 코드Neural Networks Classifier for Data Selection in Statistical Machine Translation
https://github.com/lyy1994/reformer
공식 코드https://github.com/m-resta/sg-rep
공식 코드Self-generated Replay Memories for Continual Neural Machine Translation
https://github.com/machelreid/afromt
공식 코드AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages
https://github.com/machelreid/editpro
공식 코드https://github.com/machelreid/paradise
공식 코드PARADISE: Exploiting Parallel Data for Multilingual Sequence-to-Sequence Pretraining
https://github.com/machelreid/subformer
공식 코드Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers
https://github.com/machinelearning4health/medlane
공식 코드Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation
https://github.com/madaan/PML4DC-Comparable-Data-Collection
공식 코드Practical Comparable Data Collection for Low-Resource Languages via Images
https://github.com/maharajbrahma/wat2024-multiindicmt
공식 코드NLIP_Lab-IITH Multilingual MT System for WAT24 MT Shared Task
https://github.com/mahesh-ak/SktQA
공식 코드A Case Study of Cross-Lingual Zero-Shot Generalization for Classical Languages in LLMs
https://github.com/mahfuzibnalam/terminology_evaluation
공식 코드On the Evaluation of Machine Translation for Terminology Consistency
https://github.com/mainlp/dialect-BLI
공식 코드Low-resource Bilingual Dialect Lexicon Induction with Large Language Models
https://github.com/makeshn/lobef_byte_nmt
공식 코드https://github.com/manandey/bias_machine_translation
공식 코드https://github.com/manestay/paxqa
공식 코드PAXQA: Generating Cross-lingual Question Answering Examples at Training Scale
https://github.com/mantra-inc/open-mantra-dataset
공식 코드https://github.com/manunarayanan/tulu-nmt
공식 코드https://github.com/marceloprates/Gender-Bias
공식 코드Assessing Gender Bias in Machine Translation -- A Case Study with Google Translate
https://github.com/marian-nmt/docmt23
공식 코드https://github.com/marian-nmt/marian
공식 코드https://github.com/marian-nmt/sotastream
공식 코드SOTASTREAM: A Streaming Approach to Machine Translation Training
https://github.com/marliesvanderwees/dds-nmt
공식 코드https://github.com/marxav/oteann3
공식 코드OTEANN: Estimating the Transparency of Orthographies with an Artificial Neural Network
https://github.com/marzenakrp/demetr
공식 코드https://github.com/marziehf/DataAugmentationNMT
공식 코드Data Augmentation for Low-Resource Neural Machine Translation
https://github.com/marziehf/IdiomTranslationDS
공식 코드Examining the Tip of the Iceberg: A Data Set for Idiom Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.